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Uncovering the Risks and Drawbacks Associated With the Use of Synthetic Data for Grammatical Error Correction., , , , , , и . IEEE Access, (2023)BTS: Back TranScription for Speech-to-Text Post-Processor using Text-to-Speech-to-Text., , , , , , и . WAT@ACL/IJCNLP, стр. 106-116. Association for Computational Linguistics, (2021)PU-GEN: Enhancing generative commonsense reasoning for language models with human-centered knowledge., , , , , , , и . Knowl. Based Syst., (2022)KEBAP: Korean Error Explainable Benchmark Dataset for ASR and Post-processing., , , , , , и . EMNLP, стр. 4798-4815. Association for Computational Linguistics, (2023)Length-aware Byte Pair Encoding for Mitigating Over-segmentation in Korean Machine Translation., , , , , , , , и . ACL (Findings), стр. 2287-2303. Association for Computational Linguistics, (2024)Utilization Strategy of User Engagements in Korean Fake News Detection., , , и . IEEE Access, (2022)Priming Ancient Korean Neural Machine Translation., , , , , и . LREC, стр. 22-28. European Language Resources Association, (2022)PicTalky: Augmentative and Alternative Communication for Language Developmental Disabilities., , , , , и . AACL/IJCNLP (System Demonstrations), стр. 17-27. Association for Computational Linguistics, (2022)KU X Upstage's Submission for the WMT22 Quality Estimation: Critical Error Detection Shared Task., , , , и . WMT, стр. 606-614. Association for Computational Linguistics, (2022)Generative Interpretation: Toward Human-Like Evaluation for Educational Question-Answer Pair Generation., , , , , и . EACL (Findings), стр. 2185-2196. Association for Computational Linguistics, (2024)